The code for 3.6.0 has been frozen, and baring anything critical popping up, the next Python release is scheduled for the 16th of December. After that, starting in January 2017, it will follow the normal update cycle with bug-fixes every three to six months for the next 18 months until the release of 3.7. Following the final bug-fix, it is expected that security updates will continue through December 2021.

The Python Software Foundation has provided some excellent descriptions of what’s to come. Further documentation and the following write-ups can be found at Python.org.

So what’s new in 3.6?

PEP 468 - Preserving the order of **kwargs in a function

**kwargs in a function signature is now guaranteed to be an insertion-order-preserving mapping.

The dict type now uses a “compact” representation pioneered by PyPy. The memory usage of the new dict() is between 20% and 25% smaller compared to Python 3.5.
The order-preserving aspect of this new implementation is considered an implementation detail and should not be relied upon (this may change in the future, but it is desired to have this new dict implementation in the language for a few releases before changing the language spec to mandate order-preserving semantics for all current and future Python implementations; this also helps preserve backwards-compatibility with older versions of the language where random iteration order is still in effect, e.g. Python 3.5).

PEP 487 - Simpler customization of class creation

It is now possible to customize subclass creation without using a metaclass. The new __init_subclass__ classmethod will be called on the base class whenever a new subclass is created:

class PluginBase:
    subclasses = []

    def __init_subclass__(cls, **kwargs):
        super().__init_subclass__(**kwargs)
        cls.subclasses.append(cls)

class Plugin1(PluginBase):
    pass

class Plugin2(PluginBase):
    pass

In order to allow zero-argument super() calls to work correctly from __init_subclass__() implementations, custom metaclasses must ensure that the new __classcell__ namespace entry is propagated to type.__new__ (as described in Creating the class object).

PEP 495 - Local Time Disambiguation

In most world locations, there have been and will be times when local clocks are moved back. In those times, intervals are introduced in which local clocks show the same time twice in the same day. In these situations, the information displayed on a local clock (or stored in a Python datetime instance) is insufficient to identify a particular moment in time.

PEP 495 adds the new fold attribute to instances of datetime.datetime and datetime.time classes to differentiate between two moments in time for which local times are the same:

>>> u0 = datetime(2016, 11, 6, 4, tzinfo=timezone.utc)
>>> for i in range(4):
...     u = u0 + i*HOUR
...     t = u.astimezone(Eastern)
...     print(u.time(), 'UTC =', t.time(), t.tzname(), t.fold)
...
04:00:00 UTC = 00:00:00 EDT 0
05:00:00 UTC = 01:00:00 EDT 0
06:00:00 UTC = 01:00:00 EST 1
07:00:00 UTC = 02:00:00 EST 0

The values of the fold attribute have the value 0 for all instances except those that represent the second (chronologically) moment in time in an ambiguous case.

PEP 498 - Literal String Formatting

Formatted string literals are prefixed with ‘f’ and are similar to the format strings accepted by str.format(). They contain replacement fields surrounded by curly braces. The replacement fields are expressions, which are evaluated at run time, and then formatted using the format() protocol:

>>> name = "Fred"
>>> f"He said his name is {name}."
'He said his name is Fred.'
>>> width = 10
>>> precision = 4
>>> value = decimal.Decimal("12.34567")
>>> f"result: {value:{width}.{precision}}"  # nested fields
'result:      12.35'

PEP 506 - Adding A Secrets Module To The Standard Library

The main purpose of the new secrets module is to provide an obvious way to reliably generate cryptographically strong pseudo-random values suitable for managing secrets, such as account authentication, tokens, and similar.

PEP 515 - Underscores in Numeric Literals

adds the ability to use underscores in numeric literals for improved readability.

>>> 1_000_000_000_000_000
1000000000000000
>>> 0x_FF_FF_FF_FF
4294967295

Single underscores are allowed between digits and after any base specifier. Leading, trailing, or multiple underscores in a row are not allowed.

The string formatting language also now has support for the ‘_’ option to signal the use of an underscore for a thousands separator for floating point presentation types and for integer presentation type ‘d’. For integer presentation types ‘b’ (Binary), ‘o’ (Octal), ‘x’ (Hex lower case), and ‘X’ (Hex, upper case), underscores will be inserted every 4 digits:

>>> '{:_}'.format(1000000)
'1_000_000'
>>> '{:_x}'.format(0xFFFFFFFF)
'ffff_ffff'

PEP 519 - Adding a file system path protocol

File system paths have historically been represented as str or bytes objects. This has led to people who write code which operate on file system paths to assume that such objects are only one of those two types (an int representing a file descriptor does not count as that is not a file path). Unfortunately that assumption prevents alternative object representations of file system paths like pathlib from working with pre-existing code, including Python’s standard library.

To fix this situation, a new interface represented by os.PathLike has been defined. By implementing the __fspath__() method, an object signals that it represents a path. An object can then provide a low-level representation of a file system path as a str or bytes object. This means an object is considered path-like if it implements os.PathLike or is a str or bytes object which represents a file system path. Code can use os.fspath(), os.fsdecode(), or os.fsencode() to explicitly get a str and/or bytes representation of a path-like object.

The built-in open() function has been updated to accept os.PathLike objects, as have all relevant functions in the os and os.path modules, and most other functions and classes in the standard library. The os.DirEntry class and relevant classes in pathlib have also been updated to implement os.PathLike.

The hope is that updating the fundamental functions for operating on file system paths will lead to third-party code to implicitly support all path-like objects without any code changes, or at least very minimal ones (e.g. calling os.fspath() at the beginning of code before operating on a path-like object).

Here are some examples of how the new interface allows for pathlib.Path to be used more easily and transparently with pre-existing code:

>>>
>>> import pathlib
>>> with open(pathlib.Path("README")) as f:
...     contents = f.read()
...
>>> import os.path
>>> os.path.splitext(pathlib.Path("some_file.txt"))
('some_file', '.txt')
>>> os.path.join("/a/b", pathlib.Path("c"))
'/a/b/c'
>>> import os
>>> os.fspath(pathlib.Path("some_file.txt"))
'some_file.txt'

PEP 520 - Preserving Class Attribute Definition Order

Attributes in a class definition body have a natural ordering: the same order in which the names appear in the source. This order is now preserved in the new class’s __dict__ attribute.

Also, the effective default class execution namespace (returned from type.__prepare__()) is now an insertion-order-preserving mapping.

PEP 523 - Adding a frame evaluation API to CPython

While Python provides extensive support to customize how code executes, one place it has not done so is in the evaluation of frame objects. If you wanted some way to intercept frame evaluation in Python there really wasn’t any way without directly manipulating function pointers for defined functions.

PEP 523 changes this by providing an API to make frame evaluation pluggable at the C level. This will allow for tools such as debuggers and JITs to intercept frame evaluation before the execution of Python code begins. This enables the use of alternative evaluation implementations for Python code, tracking frame evaluation, etc.

This API is not part of the limited C API and is marked as private to signal that usage of this API is expected to be limited and only applicable to very select, low-level use-cases. Semantics of the API will change with Python as necessary.

PEP 525 - Asynchronous Generators (provisional)

PEP 492 introduced support for native coroutines and async / await syntax to Python 3.5. A notable limitation of the Python 3.5 implementation is that it was not possible to use await and yield in the same function body. In Python 3.6 this restriction has been lifted, making it possible to define asynchronous generators:

async def ticker(delay, to):
    """Yield numbers from 0 to *to* every *delay* seconds."""
    for i in range(to):
        yield i
        await asyncio.sleep(delay)

The new syntax allows for faster and more concise code.

PEP 526 - Syntax for Variable Annotations (provisional)

PEP 484 introduced the standard for type annotations of function parameters, a.k.a. type hints. This PEP adds syntax to Python for annotating the types of variables including class variables and instance variables:

primes: List[int] = []

captain: str  # Note: no initial value!

class Starship:
    stats: Dict[str, int] = {}

Just as for function annotations, the Python interpreter does not attach any particular meaning to variable annotations and only stores them in the __annotations__ attribute of a class or module.

In contrast to variable declarations in statically typed languages, the goal of annotation syntax is to provide an easy way to specify structured type metadata for third party tools and libraries via the abstract syntax tree and the __annotations__ attribute.

PEP 528 - Change Windows console encoding to UTF-8

The default console on Windows will now accept all Unicode characters and provide correctly read str objects to Python code. sys.stdin, sys.stdout and sys.stderr now default to utf-8 encoding.

This change only applies when using an interactive console, and not when redirecting files or pipes. To revert to the previous behavior for interactive console use, set PYTHONLEGACYWINDOWSIOENCODING.

PEP 529 - Change Windows filesystem encoding to UTF-8

Representing filesystem paths is best performed with str (Unicode) rather than bytes. However, there are some situations where using bytes is sufficient and correct.

Prior to Python 3.6, data loss could result when using bytes paths on Windows. With this change, using bytes to represent paths is now supported on Windows, provided those bytes are encoded with the encoding returned by sys.getfilesystemencoding(), which now defaults to ‘utf-8’.

Applications that do not use str to represent paths should use os.fsencode() and os.fsdecode() to ensure their bytes are correctly encoded. To revert to the previous behavior, set PYTHONLEGACYWINDOWSFSENCODING or call sys._enablelegacywindowsfsencoding().

PEP 530 - Asynchronous Comprehensions

PEP 530 adds support for using async for in list, set, dict comprehensions and generator expressions:

result = [i async for i in aiter() if i % 2]

Additionally, await expressions are supported in all kinds of comprehensions:

result = [await fun() for fun in funcs if await condition()]

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